FUZZY CLUSTER ANALYSIS TO IDENTIFY ORE TYPES IN KHOUNI AREA, IRAN

7th International Scientific Conference - SGEM2007, www.sgem.org, SGEM2007 Conference Proceedings/ ISBN: 954-918181-2, June 11-15, 2007

ABSTRACT

Multivariate statistics analysis is one of the base stages in geochemical data
processing. In this branch of mathematics, “Hierarchical Clustering Analysis”
applied to identify the relations between the variables such as elements and
samples. Hence, different types of mineralization would define. However,
any missing or errors in entrance the data make a wrong or not clear result.
Sometimes misinformation or data errors appear because of analytical errors,
missing some information, or problems in sam pling or sample preparing.
These errors have bad effects on the statistical studies. In this situation,
interpreting the results is hard or wrong decision would make. Former
studies showed that “Fuzzy Cluster Analysis” could apply in these situations
successfully.
In this paper, the “Fuzzy Cluster Analysis”, applied to classify the anomalous
samples of Khouni Mountain, Central. Iran. 254 stream sediment samples
applied for this purpose. They have analyzed for 17 elements by ICP method;
and 90 anomalous samples identified by “×− + ns” method, a classic statistical
technique. These samples classified into groups based on the “Fuzzy” and
“Classic” classification. For each method, a dendrogram plotted to show the
result more obviously. Comparing these two methods, show that both of
them have the same result. The two diagrams are like each other at the first
glance; but the “Fuzzy dendrogram” has a higher significant level. However,
there are some misclassifications in “Classic Diagram”. In this dendrogram,
some samples don’t have meaningful relationship with other ones in the same
group. These wrong sites make it difficult to interpret the result. To avoid such problems, fuzzy method is suggested.

Keywords: Fuzzy Cluster Analysis, Multivariate Analysis, Geochemical
Anomalies